sortedcontainers VS more-itertools

If you like Python, the library sortedcontainers as a clear, well documented, yet short source code that is a joy to read for a non trivial problem:

https://github.com/grantjenks/python-sortedcontainers/blob/m...

See for yourself. Looks like sortedset uses sortedlist under the hood, which itself uses a list of lists under the hood.

You could use http://www.grantjenks.com/docs/sortedcontainers/ instead!

Even the Gentoo package repository manages fine with a two-level hierarchy. There's also a Python library, sortedcontainers, that suggests two-level trees are pretty good at any reasonable human-scale (and beyond), even while fixed-arity trees are asymptotically optimal.

It's a good question and to be accurate, depending on the benchmark, Mongita is about the same speed at SQLite to several-times slower.

There is less happening algorithmically than you would think. Where the tricky slow bits do exist, they have largely fallen into the happy-path of fast data structures in the Python language/stdlib. I also use sortedcontainers for indexes which helped quite a bit (http://www.grantjenks.com/docs/sortedcontainers/).

If you're curious, the benchmark code is in the repo: https://github.com/scottrogowski/mongita/blob/master/benchma...

I’d like to add sortedcontainers. I use it all the time. It basically does what it says on the tin. Other than the SortedList, the fact that the container is sorted only comes into play when you iterate over it or perform a bisect left/right.

I'd bet that reading through more-itertools would be a good exercise.

check out the code examples in itertools and the source code of more-itertools if you want to see cases where next and iter get used by themselves.

from itertools import islice # Copied from the more-itertools library (MIT license) # https://github.com/more-itertools/more-itertools def batched(iterable, n): "Batch data into lists of length n. The last batch may be shorter." # batched('ABCDEFG', 3) --> ABC DEF G if n < 1: raise ValueError('n must be at least one') it = iter(iterable) while (batch := list(islice(it, n))): yield batch

more_itertools.chunked

I've had a tab open to more-itertools on github for weeks; maybe I should go read it...

The popular more-itertools library implements (among many others) a chunked method which yields lists of size n from an iterator. There is also the ichunked method which yields iterators of size n instead of lists.

There's a function called consecutive_groups in the more-itertools library that will do this for you efficiently.

Here are some that might answer your question: - algorithms is a library which contains many of the most useful algorithms for sorting, searching, working with trees, math algorithms like factorials, prime finders and many more - data classes to save you the trouble of writing everytime special methods in a class like init, repr, set, get - box allows the use of dot on dictionaries to access the keys - more-itertools for more routines to operate on iterables than those itertools provide.